Today's high-assurance communications systems require near real-time transmissions of highly consistent data streams. Acquisition and maintenance of the subject data is an important and often difficult task for many modems. This is especially true for waveforms having higher data rates that employ complex modulations such as continuous-phase modulation (CPM). In ultra-high frequency (UHF) satellite communication (SATCOM) military waveform standards, several higher data rate waveforms are defined, for example MIL-STD-188-181B.
As such, modern systems require the ability to detect improprieties in data streams in order to take corrective measures to maintain the integrity of the communicated data. One possible source of data corruption may arise from carrier wave dropout. Carrier wave dropout may result from signal interference due to environmental noise or device failure. Regardless of the nature of the dropout, systems must be able to detect the dropout, reacquire the carrier wave, and discern between corrupted data resulting from the dropout and the desired accurate data.
Kalman filtering may be used to monitor carrier wave power and provide estimated power values based on historical state information when interference with a received signal occurs. However, certain Kalman filters, such as 0-order Kalman filters, are designed to measure constant values. As such, when a carrier power drops significantly, a 0-order Kalman filter diverges from steady-state and is no longer able to accurately track and estimate the signal.
Therefore, it would be desirable to provide a system and method for detecting carrier dropout utilizing a Kalman filter.